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Abstract

Ongoing monitoring of complex, mixed species environments is a challenging task. In this study, the potential of acoustic and catch data collected aboard a commercial fishing vessel, in combination with geostatistical variance estimates, are explored as a means to derive information on the distribution and abundance of key species groups within selected fishing regions. The FV Carolina M, a trap fishing vessel which operates in waters off Broome, Western Australia, in the Northern Demersal Scalefish Fishery, was equipped with Simrad ES70 echosounders, operated at 38 and 120 kHz. Optical recordings of catch were also obtained, in addition to the acoustic data, during routine fishing operations in 2014. Three regions, where both optical and acoustic datasets were available, were selected for analysis. Geostatistical conditional simulations were used to combine acoustic density information with species composition proportions and length distributions within the catch. For each of the input datasets 250 simulations were conducted, from which individual and combined sampling CVs were derived. Conversion of acoustic densities into abundance estimates was achieved through application of target strength to length relationships (TS-L). Where TS-L was unavailable in the literature for a particular species it was estimated through a Kirchhoff-ray mode model. TS-L equations were estimated for rankin cod (Epinephelus multinotatus)(TSRC = 20 log10(L) − 79.6), triggerfish (Balistidae) (TSTF = 20 log10(L) − 77.7) and spangled emperor (Lethrinus nebulosus) (TSSE = 20 log10(L) − 70.8) at 38 kHz. Sampling error was found to be generally low for catch proportions (<12%) and acoustic densities (<10%). Total sampling error CV for species group abundances within each of the three regions was 9%–38%, which is similar to typical estimates reported for acoustic surveys.

Item Type:	Article
Authors/Creators:	Gastauer, S and Scoulding, B and Parsons, M
Keywords:	fisheries acoustics, geostatistics, target strength, NDSF, fishing vessel, error estimates
Journal or Publication Title:	Fisheries Research
Publisher:	Elsevier Science Bv
ISSN:	0165-7836
DOI / ID Number:	https://doi.org/10.1016/j.fishres.2017.07.008
Copyright Information:	Copyright 2017 Elsevier B.V.
Related URLs:	Google Scholar: Gastauer, S
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